Method and system for compression of a real-time surveillance signal

Abstract

An embodiment provides a method for compression of a real-time surveillance signal. This method includes receiving a signal from a monitoring device and analyzing the signal to be monitored to compute spectral content of the signal. This method also includes computing the information content of the signal and determining a count of a number of coefficients to be used to monitor the signal. This method includes deploying a strategy for computing a plurality of coefficients based on the spectral content of the signal and the count of the number of coefficients to be used for monitoring the signal. This method further includes monitoring the signal and resetting the system in the case of above-threshold changes in a selected portion of the plurality of coefficients.

What is claimed is: 
     
       1. A method for compression of a real-time surveillance signal, comprising:
 receiving a signal from a monitoring device; 
 analyzing the signal to compute spectral content of the signal; 
 computing information content of the signal, wherein computing the information content comprises computing a number of bits of information in the signal; 
 automatically selecting, using a processor, how many coefficients to use to represent the signal to be monitored based on the information content of the signal, wherein selecting how many coefficients comprises selecting a number of coefficients that is greater than the number of bits of information multiplied by a constant; 
 deploying a strategy for computing a plurality of coefficients based on the spectral content of the signal and how many coefficients were determined to be used for representing the signal; and 
 monitoring the signal and resetting the system in case of above-threshold changes in a selected portion of the plurality of coefficients. 
 
     
     
       2. The method of  claim 1 , wherein the monitoring device comprises a video recorder, surveillance system, camera, mobile device, or any combination thereof. 
     
     
       3. The method of  claim 1 , wherein analyzing the signal to compute spectral content comprises:
 determining the full spectrum of the signal; 
 determining the normalized spectrum of the signal; and 
 determining the cumulative spectrum of the signal. 
 
     
     
       4. The method of  claim 3 , wherein determining the cumulative spectrum of the signal comprises utilizing the normalized spectrum to compute the cumulative magnitude of the spectrum at different frequencies. 
     
     
       5. The method of  claim 1 , wherein computing the information content of the signal comprises using Shannon's method to measure the number of bits of information provided in a channel. 
     
     
       6. The method of  claim 1 , wherein selecting how many coefficients comprises selecting a count of a number of task-specific cepstral coefficients (TSCCs) to represent the signal by determining a lowest integer that is greater than the number of bits per channel, bits per sensor, or bits per image, or any combinations thereof. 
     
     
       7. The method of  claim 1 , wherein deploying a strategy for computing a plurality of coefficients comprises selecting a deployment strategy from an Optimal-Spread approach, a Median-Band approach, a Jitter approach, an anticipatory approach, a tiled approach, or any combination thereof. 
     
     
       8. The method of  claim 1 , wherein monitoring the signal comprises:
 iteratively calculating the values of the plurality of coefficients; and 
 comparing the values of each of the plurality of coefficients to the previous value to verify that a predetermined percentage of the plurality of coefficients remain within a predetermined range. 
 
     
     
       9. The method of  claim 1 , wherein resetting the system in response to significant changes in magnitude of the coefficients comprises sampling the signal at a higher bandwidth and restarting the initial training phase by performing a full-spectrum analysis of the signal. 
     
     
       10. The method of  claim 9 , wherein significant changes in magnitude comprise changes in any, all, or a subset of the coefficients which are above the predetermined threshold value for allowable changes, as specified by the user. 
     
     
       11. The method of  claim 9 , wherein sampling the signal at a higher bandwidth comprises instantly replacing the low-bandwidth monitoring with higher-bandwidth or full video transmission monitoring. 
     
     
       12. A computer system for compression of a real-time surveillance signal, comprising:
 a processor that is adapted to execute stored instructions; 
 a memory device that stores instructions that are executable by the processor, the instructions comprising:
 a training module to analyze a signal to be monitored to compute spectral content of the signal, compute information content of the signal based on a number of bits of information contained in the signal, automatically select how many coefficients to use to monitor the signal based on the information content of the signal, the how many coefficients selected based on a lowest integer greater than the number of bits multiplied by a constant, and deploy a strategy for computing a plurality of coefficients based on the spectral content of the signal and how many coefficients were determined to be used for monitoring the signal; and 
 a deployment module to monitor the signal and reset the system in case of above-threshold changes in a selected portion of the plurality of coefficients. 
 
 
     
     
       13. The system of  claim 12 , wherein the deployment module comprises code configured to repeatedly calculate the changes in magnitude of the coefficients in a feedback loop in which the current value of each of the plurality of coefficients is compared to the previous value of each of the plurality of coefficients. 
     
     
       14. The system of  claim 13 , wherein the continuous feedback loop is uninterrupted unless the change in magnitude of the coefficients is above a predetermined threshold value, in which case the system is restarted. 
     
     
       15. A non-transitory computer-readable medium, comprising code configured to direct a processor to:
 utilize a training phase to analyze the signal to be monitored to compute spectral content, compute the information content of the signal, automatically select how many coefficients to use to monitor the signal based on the information content of the signal, and deploy a strategy for computing a plurality of coefficients based on the spectral content of the signal and how many coefficients were determined to be used for monitoring the signal; and 
 utilize a deployment phase to monitor the signal and reset the system in the case of above-threshold changes in a selected portion of the plurality of coefficients. 
 
     
     
       16. The system of  claim 12 , wherein the deployment module is to indicate the reset to the training module, and wherein based on the indicated reset, the training module is to restart a training phase, wherein in the training phase, the training module is to again analyze the signal to compute the spectral content, compute the information content of the signal, determine how many coefficients to use to monitor the signal, and deploy the strategy for computing the plurality of coefficients. 
     
     
       17. The method of  claim 1 , wherein monitoring the signal comprises generating the plurality of coefficients according to the deployed strategy, detecting the above-threshold changes in the selected portion of the plurality of coefficients, and based on the detecting, restarting a training phase to again generate the plurality of coefficients. 
     
     
       18. The method of  claim 17 , further comprising based on the detecting, again determining the strategy based on the information content of the signal. 
     
     
       19. The method of  claim 1 , wherein the constant is one. 
     
     
       20. The system of  claim 12 , wherein the constant is one.